Corpus ID: 15959545

Automatic Design of Balanced Board Games

@inproceedings{Marks2007AutomaticDO,
  title={Automatic Design of Balanced Board Games},
  author={Joe Marks and Vincent Hom},
  booktitle={AIIDE},
  year={2007}
}
AI techniques are already widely used in game software to provide computer-controlled opponents for human players. However, game design is a more-challenging problem than game play. Designers typically expend great effort to ensure that their games are balanced and challenging. Dynamic game-balancing techniques have been developed to modify a game-engine's parameters in response to user play. In this paper we describe a first attempt at using AI techniques to design balanced board games like… Expand
Evaluating Competitive Game Balance with Restricted Play
TLDR
This work argues for a formulation in which carefully restricted agents are played against standard agents, and develops this restricted-play balance framework, and evaluates its utility by building a tool capable of calculating measures of balance for a large family of games. Expand
AI-based playtesting of contemporary board games
TLDR
Four different game-playing agents that embody different playing styles are defined and used to analyze Ticket to Ride, showing which cities on the map are most desirable, and that the relative attractiveness of cities is remarkably consistent across numbers of players. Expand
AI as Evaluator: Search Driven Playtesting of Modern Board Games
TLDR
It is led to the conclusion that large scale simulation utilizing artificial intelligence can offer valuable information regarding modern board games and their designs that would ordinarily be prohibitively expensive or time-consuming to discover manually. Expand
Evolutionary Learning and Search-Based Content Generation in Computer Games
TLDR
This thesis focuses on the application of Computational Intelligence, and in particular Evolutionary Algorithms, to computer games, and investigates different learning paradigms which can support the development of non-player characters. Expand
Recombinable Game Mechanics for Automated Design Support
TLDR
This work proposes an architecture based on the event calculus, a logical representation designed for reasoning about time in an elaboration-tolerant way, meaning that designs can be changed by adding or removing sets of axioms rather than modifying brittle hard-coded representations. Expand
Improving Game Design through Responsive Configuration and Procedural Generation
TLDR
This thesis investigates a method by which game configuration and creation might be automated in such a way that a numerical rating could be assigned to any given game feature, thereby allowing the enjoyability of a game feature to be gauged in a more objective way. Expand
Evolvestone: An evolutionary generator of balanced digital collectible card games
Automated game generation has become desirable to keep up with the ever increasing demand for new and fun digital games. This is a challenging task that requires a huge amount of creativity fromExpand
Chapter 6 Rules and mechanics
Rules are at the core of many games. So how about generating them? This chapter discusses various ways to encode and generate game rules, and occasionally game entities that are strongly tied toExpand
Winning Isn ’ t Everything : Training Agents to Playtest Modern Games
Recently, there have been several high-profile achievements of agents learning to play games against humans and beat them. We propose an approach that instead addresses how the player experiences theExpand
Automatic generation of game elements via evolution
  • D. Ashlock
  • Computer Science
  • Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games
  • 2010
TLDR
A system for automatically producing puzzles for use in game design that incorporates an evolutionary algorithm that optimizes the puzzle to a specified level of difficulty and can be generalized to puzzles of remarkable complexity by simply upgrading the dynamic programming algorithm used in the fitness function. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 19 REFERENCES
DIFFICULTY SCALING OF GAME AI
“Difficulty scaling” is the automatic adaptation of a game, to adapt the challenge a game poses to a human player. In general, a game of which the challenge level matches the skill of the humanExpand
METAGAME : A New Challenge for Games and Learning
In most current approaches to Computer Game-Playing, including those employing some form of machine learning, the game analysis mainly is performed by humans. Thus, we are sidestepping largely theExpand
General Game Playing: Overview of the AAAI Competition
TLDR
An overview of the technical issues and logistics associated with this summer's competition, as well as the relevance of general game playing to the long range-goals of artificial intelligence, are overviewed. Expand
AI for Dynamic Difficulty Adjustment in Games
Video Games are boring when they are too easy and frustrating when they are too hard. While most singleplayer games allow players to adjust basic difficulty (easy, medium, hard, insane), theirExpand
Challenge-sensitive action selection: an application to game balancing
TLDR
This work presents an innovative use of reinforcement learning techniques to build intelligent agents that adapt their behavior in order to provide dynamic game balancing and applies it to a real-time fighting game, obtaining good results. Expand
Fundamentals of Game Design
TLDR
This in-depth resource offers a first-hand look into the process of designing a game, from initial concept to final tuning, and comes with engaging end-of-chapter exercises, design worksheets, and case studies. Expand
Online Coevolution for Action Games
TLDR
This work presents four different methods to do online evolution of the agents: using game specific information; merging offline-evolved data with online evolution; using online data only; and using them together. Expand
Heuristic Programming in Artificial Intelligence
The first Soviet Computer Olympiad 2nd Computer Olympiad reports Go intellect wins two gold medals databases in Awari an architecture for a sophisticated mechanical bridge player design andExpand
Dynamic Game Balancing: An Evaluation of User Satisfaction
TLDR
An evaluation by human players of dynamic game balancing approaches indicates that adaptive approaches are more effective, and enumerates some issues encountered in evaluating users' satisfaction, in the context of games, and depicts some learned lessons. Expand
Genetic programming - on the programming of computers by means of natural selection
  • J. Koza
  • Computer Science
  • Complex adaptive systems
  • 1993
TLDR
This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming. Expand
...
1
2
...